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This paper addresses the prediction of error floors of low-densityparity-check (LDPC) codes with variable nodes of constant degree in theadditive white Gaussian noise (AWGN) channel. Specifically, we focus on theperformance of the sum-product algorithm (SPA) decoder formulated in thelog-likelihood ratio (LLR) domain. We hypothesize that several published errorfloor levels are due to the manner in which decoder implementations handled theLLRs at high SNRs. We employ an LLR-domain SPA decoder that does not saturatenear-certain messages and find the error rates of our decoder to be lower by atleast several orders of magnitude. We study the behavior of trapping sets (ornear-codewords) that are the dominant cause of the reported error floors.  We develop a refined linear model, based on the work of Sun and others, thataccurately predicts error floors caused by elementary tapping sets forsaturating decoders. Performance results of several codes at several levels ofdecoder saturation are presented.

Error Floor Approximation for LDPC Codes in the AWGN Channel